Can Someone Help Me Understand How Neural Nets Actually Process Inputs? Especially Activation Functions and Backpropagation? [D]
I am an enthusiast coder. I don't work in coding professionally but it has been a hobby of mine for about 6-7 years now. I've taken a lot of YouTube classes on Machine Learning and I am pretty good at training Pytorch models for image identification and tabular data predictions. I've created several Jupyter notebooks using Pytorch to train a model with a given data set and make accurate predictions or identifications of images. What I'm trying to say is I understand a lot about coding and how to build apps on top of ml systems.
The problem is that I don't understand how the actual neural network works. It's a black box to me.
My Current Understanding of Components in A Neural Net:
Weights: A table full of numbers which are added with the individual parameters of the input.
Model: Conta…